Guaranteeing Risk Levels in Chance-Constrained Optimization under Time-Varying Distributions

The core message of this paper is to establish bounds on the violation probability of an optimal solution of the robust scenario problem for guaranteeing prescribed risk levels in chance-constrained optimization when the scenarios are generated from time-varying distributions, for both convex and non-convex feasible regions.